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Measuring and modelling leaf diffusive conductance in juvenile silver birch, Betula pendula

机译:桦木桦的叶片扩散导度的测量和建模

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Leaf diffusive conductance for water (g(l)) and twig xylem pressure (psi(xt)) was measured in juvenile silver birch, Betula pendula, under field conditions in southern Sweden. Data from one site were used to parameterise two different multiplicative models for g(l) (dependent data), and measurements from another site were used to validate these models (independent data). In addition, experiments were performed in controlled environments to validate the g(l) response functions used in the models. The driving variables in the D-model were photosynthetic photon flux density, air temperature and water vapour pressure deficit of the air (D-a), while the DH-model also included the accumulated hours after sunrise each day with D-a above a certain threshold (H). Both models satisfactorily predicted the variation in g(l) in dependent as well as in independent data, and the g(l) response functions used were supported by the experiments in controlled environments. The DH-model was more successful in predicting g(l) than the D-model by accounting for the observation that g(l) was lower at higher H under similar weather conditions. There was a considerable variation in maximum g(l) during the season, as well as between the two sites. On relatively warm and dry days psi(xt) rapidly declined during the morning and then stabilized around a constant value until the late afternoon, with the stomatal regulation effectively preventing psi(xt) from decreasing below this value. We suggest that these models could be used to simulate the g(l) in juvenile birch if maximum g(l) is locally estimated and if the response functions are not extrapolated beyond the climate range for this study.
机译:在瑞典南部的田野条件下,在幼年桦桦桦中测量了水的叶扩散导度(g(l))和嫩枝木质部压力(psi(xt))。来自一个站点的数据用于参数化g(l)的两个不同的乘法模型(相关数据),而来自另一个站点的测量值用于验证这些模型(独立数据)。另外,在受控环境中进行了实验以验证模型中使用的g(l)响应函数。 D模型的驱动变量是光合作用的光子通量密度,空气温度和空气中的水蒸气压亏缺(Da),而DH模型还包括每天日出后的累积小时数,Da超过特定阈值(H )。两种模型都令人满意地预测了相关数据和独立数据中g(l)的变化,并且在受控环境中的实验支持了所使用的g(l)响应函数。 DH模型在预测g(l)方面比D模型更成功,原因是观察到在类似天气条件下,较高H时g(l)较低,从而引起观察。整个季节以及两个地点之间的最大g(l)都有很大的差异。在相对温暖和干燥的日子里,psi(xt)在早上迅速下降,然后稳定在恒定值附近直到下午晚些时候,气孔调节有效地防止了psi(xt)降至该值以下。我们建议,如果最大g(l)是局部估计的,并且响应函数未超出本研究的气候范围,则可以将这些模型用于模拟幼年桦的g(l)。

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